GRT_LABELLED_CLASSIFICATION_DATA_FILE_V1.0
DatasetName: Iris
InfoText: This is perhaps the best known database to be found in the pattern recognition literature. The data set contains 3 classes of 50 instances each with 4 features, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly separable from each other. This dataset can be found at the UCL Machine Learning Repository: http://archive.ics.uci.edu/ml/datasets/Iris.  The 4 features are: (1) Sepal Length in cm, (2) Sepal Length in cm, (3) Petal Length in cm, (4) Petal Width in cm.
NumDimensions: 4
TotalNumTrainingExamples: 150
NumberOfClasses: 3
ClassIDsAndCounters: 
1	50	Iris_Setosa
2	50	Iris_Versicolour
3	50	Iris_Virginica
UseExternalRanges: 0
LabelledTrainingData:
1	5.1	3.5	1.4	0.2
1	4.9	3	1.4	0.2
1	4.7	3.2	1.3	0.2
1	4.6	3.1	1.5	0.2
1	5	3.6	1.4	0.2
1	5.4	3.9	1.7	0.4
1	4.6	3.4	1.4	0.3
1	5	3.4	1.5	0.2
1	4.4	2.9	1.4	0.2
1	4.9	3.1	1.5	0.1
1	5.4	3.7	1.5	0.2
1	4.8	3.4	1.6	0.2
1	4.8	3	1.4	0.1
1	4.3	3	1.1	0.1
1	5.8	4	1.2	0.2
1	5.7	4.4	1.5	0.4
1	5.4	3.9	1.3	0.4
1	5.1	3.5	1.4	0.3
1	5.7	3.8	1.7	0.3
1	5.1	3.8	1.5	0.3
1	5.4	3.4	1.7	0.2
1	5.1	3.7	1.5	0.4
1	4.6	3.6	1	0.2
1	5.1	3.3	1.7	0.5
1	4.8	3.4	1.9	0.2
1	5	3	1.6	0.2
1	5	3.4	1.6	0.4
1	5.2	3.5	1.5	0.2
1	5.2	3.4	1.4	0.2
1	4.7	3.2	1.6	0.2
1	4.8	3.1	1.6	0.2
1	5.4	3.4	1.5	0.4
1	5.2	4.1	1.5	0.1
1	5.5	4.2	1.4	0.2
1	4.9	3.1	1.5	0.1
1	5	3.2	1.2	0.2
1	5.5	3.5	1.3	0.2
1	4.9	3.1	1.5	0.1
1	4.4	3	1.3	0.2
1	5.1	3.4	1.5	0.2
1	5	3.5	1.3	0.3
1	4.5	2.3	1.3	0.3
1	4.4	3.2	1.3	0.2
1	5	3.5	1.6	0.6
1	5.1	3.8	1.9	0.4
1	4.8	3	1.4	0.3
1	5.1	3.8	1.6	0.2
1	4.6	3.2	1.4	0.2
1	5.3	3.7	1.5	0.2
1	5	3.3	1.4	0.2
2	7	3.2	4.7	1.4
2	6.4	3.2	4.5	1.5
2	6.9	3.1	4.9	1.5
2	5.5	2.3	4	1.3
2	6.5	2.8	4.6	1.5
2	5.7	2.8	4.5	1.3
2	6.3	3.3	4.7	1.6
2	4.9	2.4	3.3	1
2	6.6	2.9	4.6	1.3
2	5.2	2.7	3.9	1.4
2	5	2	3.5	1
2	5.9	3	4.2	1.5
2	6	2.2	4	1
2	6.1	2.9	4.7	1.4
2	5.6	2.9	3.6	1.3
2	6.7	3.1	4.4	1.4
2	5.6	3	4.5	1.5
2	5.8	2.7	4.1	1
2	6.2	2.2	4.5	1.5
2	5.6	2.5	3.9	1.1
2	5.9	3.2	4.8	1.8
2	6.1	2.8	4	1.3
2	6.3	2.5	4.9	1.5
2	6.1	2.8	4.7	1.2
2	6.4	2.9	4.3	1.3
2	6.6	3	4.4	1.4
2	6.8	2.8	4.8	1.4
2	6.7	3	5	1.7
2	6	2.9	4.5	1.5
2	5.7	2.6	3.5	1
2	5.5	2.4	3.8	1.1
2	5.5	2.4	3.7	1
2	5.8	2.7	3.9	1.2
2	6	2.7	5.1	1.6
2	5.4	3	4.5	1.5
2	6	3.4	4.5	1.6
2	6.7	3.1	4.7	1.5
2	6.3	2.3	4.4	1.3
2	5.6	3	4.1	1.3
2	5.5	2.5	4	1.3
2	5.5	2.6	4.4	1.2
2	6.1	3	4.6	1.4
2	5.8	2.6	4	1.2
2	5	2.3	3.3	1
2	5.6	2.7	4.2	1.3
2	5.7	3	4.2	1.2
2	5.7	2.9	4.2	1.3
2	6.2	2.9	4.3	1.3
2	5.1	2.5	3	1.1
2	5.7	2.8	4.1	1.3
3	6.3	3.3	6	2.5
3	5.8	2.7	5.1	1.9
3	7.1	3	5.9	2.1
3	6.3	2.9	5.6	1.8
3	6.5	3	5.8	2.2
3	7.6	3	6.6	2.1
3	4.9	2.5	4.5	1.7
3	7.3	2.9	6.3	1.8
3	6.7	2.5	5.8	1.8
3	7.2	3.6	6.1	2.5
3	6.5	3.2	5.1	2
3	6.4	2.7	5.3	1.9
3	6.8	3	5.5	2.1
3	5.7	2.5	5	2
3	5.8	2.8	5.1	2.4
3	6.4	3.2	5.3	2.3
3	6.5	3	5.5	1.8
3	7.7	3.8	6.7	2.2
3	7.7	2.6	6.9	2.3
3	6	2.2	5	1.5
3	6.9	3.2	5.7	2.3
3	5.6	2.8	4.9	2
3	7.7	2.8	6.7	2
3	6.3	2.7	4.9	1.8
3	6.7	3.3	5.7	2.1
3	7.2	3.2	6	1.8
3	6.2	2.8	4.8	1.8
3	6.1	3	4.9	1.8
3	6.4	2.8	5.6	2.1
3	7.2	3	5.8	1.6
3	7.4	2.8	6.1	1.9
3	7.9	3.8	6.4	2
3	6.4	2.8	5.6	2.2
3	6.3	2.8	5.1	1.5
3	6.1	2.6	5.6	1.4
3	7.7	3	6.1	2.3
3	6.3	3.4	5.6	2.4
3	6.4	3.1	5.5	1.8
3	6	3	4.8	1.8
3	6.9	3.1	5.4	2.1
3	6.7	3.1	5.6	2.4
3	6.9	3.1	5.1	2.3
3	5.8	2.7	5.1	1.9
3	6.8	3.2	5.9	2.3
3	6.7	3.3	5.7	2.5
3	6.7	3	5.2	2.3
3	6.3	2.5	5	1.9
3	6.5	3	5.2	2
3	6.2	3.4	5.4	2.3
3	5.9	3	5.1	1.8
